{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.ticker as mticker\n",
    "import matplotlib\n",
    "from mpl_finance import candlestick_ohlc\n",
    "from datetime import datetime\n",
    "import seaborn as sns\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-05-23</td>\n",
       "      <td>277.760010</td>\n",
       "      <td>279.910004</td>\n",
       "      <td>274.000000</td>\n",
       "      <td>279.070007</td>\n",
       "      <td>279.070007</td>\n",
       "      <td>5953100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-05-24</td>\n",
       "      <td>278.399994</td>\n",
       "      <td>281.109985</td>\n",
       "      <td>274.890015</td>\n",
       "      <td>277.850006</td>\n",
       "      <td>277.850006</td>\n",
       "      <td>4176700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-05-25</td>\n",
       "      <td>277.630005</td>\n",
       "      <td>279.640015</td>\n",
       "      <td>275.609985</td>\n",
       "      <td>278.850006</td>\n",
       "      <td>278.850006</td>\n",
       "      <td>3875100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-05-29</td>\n",
       "      <td>278.510010</td>\n",
       "      <td>286.500000</td>\n",
       "      <td>276.149994</td>\n",
       "      <td>283.760010</td>\n",
       "      <td>283.760010</td>\n",
       "      <td>5666600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-05-30</td>\n",
       "      <td>283.290009</td>\n",
       "      <td>295.010010</td>\n",
       "      <td>281.600006</td>\n",
       "      <td>291.720001</td>\n",
       "      <td>291.720001</td>\n",
       "      <td>7489700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date        Open        High         Low       Close   Adj Close  \\\n",
       "0  2018-05-23  277.760010  279.910004  274.000000  279.070007  279.070007   \n",
       "1  2018-05-24  278.399994  281.109985  274.890015  277.850006  277.850006   \n",
       "2  2018-05-25  277.630005  279.640015  275.609985  278.850006  278.850006   \n",
       "3  2018-05-29  278.510010  286.500000  276.149994  283.760010  283.760010   \n",
       "4  2018-05-30  283.290009  295.010010  281.600006  291.720001  291.720001   \n",
       "\n",
       "    Volume  \n",
       "0  5953100  \n",
       "1  4176700  \n",
       "2  3875100  \n",
       "3  5666600  \n",
       "4  7489700  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('TSLA.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "date = [datetime.strptime(d, '%Y-%m-%d') for d in df['Date']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "candlesticks = list(zip(mdates.date2num(date),df['Open'],\n",
    "                   df['High'],df['Low'],df['Close'],df['Volume']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SJptKEuvVsnVooBic5oCVZ95YtXOpWlZ5v0HuVY9dz7q+9b4eU2k/tz31Da567HqGN25oeH9hm7N8BdMXLoq6GaFyvyfVbB0aOOBx6/rW13yciIjUJ+oR3bI1mYDDgX8zxrQBbcAvgU8BWGv3FaY4rzLGdFAoLxRB2yPhjDBcNGUKw5//RN29w3OWr2Bb7xp2rO0NuIVSj7BrIc9ZvoJJW37pawqmSBxUS34XVSIfvwE2+A+MKz2vs58P/OuvGBjLZ8zn/MMa3nczpS2hoXuNdDMeJyIi3kQa6FaryQScVOVxjwPHh9KomHNn7PR7geeUmKj0u19Rl6oQf2VDZpx6itbCSOLUqjnrTCH+7i8eqJh1OGilI3NhKbeW31k20jWWa0obwpC0OsJBct7TdX3rJ0yfFxGR4EU9oitNVHphUc+FhrsG5AnLV1TM3izBcI43Sy4oe3+lsiEiraJ0vXu9gui4CzpgKffanPXEcHegzyX+1bNO2719jvBn84iItDIFuglQDHYAMhnI5bTWskWEkcQlbdMGpTUFnQzKS2dRpWRCK8+8MbB2SHL4+fw5n1dnFBfyHSOaGSUiEh4FugkwIdjJ5Zi+cBEzFy1uejs2DW7mhMLa3iieX4LRytMGJT3KBRnlRlRLg1Nn6m89o69bhwaKWZuj4GRnP/3ISit+4qnRZTJx4XQS1pM92Z0E7RPHX6BZOCIiTaBANwHc5RmiHMktl/glLm1LOvXqi9Tv/W85hzMOf3fZ+0rPW5VKCSVFEhMXpaVjzekk9JsErTQ7toJcEZHmUKCbAE7tRmckdVvvmqa3wZl29ejAE1zpygPmtE3TYRtT6cIn6BqU7jXWc5av0PsmiVRP1uOgOIHyowNP+BoZDrL2eGnHWOfucUYntympUYjc504+/d6y25Q7/sWlRwnLjC0ikgYKdMWTWmUQFCyFw+lICIo7azdoGrMkU2nW49mHHlV2u3IZboOa+ut3ZDjIJFInZI9ji6sT7JIfvsbTnz4rsaPUSVB67ixVKalUGHkWRETEGwW6IiKSaG8/6sSapbOcBEBDe4YTvVTAGTWcU5Iv4ennHoyyWSIiIrEzKeoGiH9RJ/aI+vklGM8suZAda3vZcsVlUTdFWlxYU5GXnXYNC2bPOyArclLXSC6YPW9CnWCdi0VERCpToJtAzZxqWu4CVFNdk6tcwjBNrZOolU5FDoMzElrvOtbbF89gXd96rnrs+uJtUY8M61zsTWkyqEY4n4NLH/rchNuj/iyIiMiBFOgmSBS99824AJXmmbN8BdMXLoq6GSJ1cXe8+Q1cndFd94ioH6OT24CJeQrqGRl2OpuCzlKvQKu8LVdcxsDKWwKbueJ8DkoldZaAiEiaaY1ugqj3XkRaSWmWcHcd25727ooJgMLWSFBZKdt5oxnQ4x5oFTPIZzLsWNtbfE/DViuJlIiIpJdGdMWTRqf9iYj4VS5IqZUBvpqgRj0bDSrLBbRj/f0N7TPuirNJcvm0YEEHnmGWnIqynJWIiNRPga540ui0P4kX97TJoKdQivjRNbWNC095H9lsD11Ty08LDUrcRz1r0fTkysJcZrN1aKB4nuwcy9XYWkRE4kJTl2Nu0+DmxF6ctbnqPCqYihdnyqC7PIlIFDrbO8kszQCQuzbHCPvLBDnnkErnj1YL/JL6XZBkTi3mR8+dyZXbz+CmBYuL9ZNLE1JV07l7nNHJbZoVJSLSRAp0Y27r0EBiL25K6zxK/Kg8icRZrXNIUs+Nbs46ZKBp61ajEtb5phiMDjwR+KyjalPle9q7i+vFK3E6ay754WvMWf6/A22biIhUp0C3xVUbdXUuHtb1raenvZvTjzw1iiZKiJTgTMSbIEbkyo1Au9eqpj1hUvdJJ9ccpa9HI+u2G7HstGuKo7uVpLnjQkQk7hToxliYvdSOaiMm7ouGIC4gGs0qKsHQKK4kmZdRtDBctGY7u790ZUOjyGkYgW5Us2f6hBFYi4hIMijQjbFm9VI3I/Bxpue1TZmiHu6IqbNBkszLKFpQSme8KFBNnjACa/fIfKutExcRSRIFutKUwEe1DEUkaZRnQMpxd3io80NEJL4U6EYo7lN5nSmCzs/10DRZEWmUs4wD4NGBJ3zlC2h0xE3nsOC5j2ncvwdFRCS5FOhGaKy/P9Zf8KVTBB947kHf+4jz6xORZCjNF+AneG10xE3nsOC5j2ncvwdFRCS5JkXdAJFW5B4hV11FkepK/140XVRERERq0YiuVBWnRBtpmuLmZNFuVlKdsGwa3KygQ0KXlr8XERERaR6N6EpVcQpixvr7o25Cag1v3FDX47YODQTcEpGJtEY2nbZccRnPLLmQHWt72XLFZb4eu2lwc0itqi7Mz2K952AREalMga54FqfRXQmWOhEkrtIyi6MSd33XVqr16s7A7ycb/1WPXc9tT32Dqx67PoxmVRXmZ1HnYBGR4GnqsngWp9Hdeqmer4jEiXMeKrc0I4jM92lTT315zQoQEWlNCnRjIE1rT8PiBKg7H3m47gB10+BmJqueb920HlckPOW+A5y1ydIYfb8GT9ctIpIEmrocA5qyVNt4mQDV75qmrUMDxamBbVOmTFjn1crro7ZccZmndXLOetxy6+OiWjMnIumgc0iy6LpFRJJAgW6MOVPVNGWNCQGqw88X7VWPXc+6vvXcfu5Mpi9cxJzlKyYkUorqSzsO657LdSJUU5qAqtaaOV3AikgtjSS2S/p3pdfOxqjpXC4iSaOpyxHwOgVU09b2m7N8Bdt61zBz0eK6ptDWs66rGZIyFfiqx65naM8w3+9bTw5Y17eenvZuTj/y1JrHduvQQGJep8RbHDqGJF6GN25g2WnXhFZ6ylknHWYQ7bezMSo6l4tI0mhENwIqydKYrUMDxR7wZ5Zc2HAveFJ606PkBLG5iNsh6eJ3yYAusqVU2LNxlp12DQtmz2v5jmdnVlQU2a5FROqlQFcSqd7SFA7nS/vShz6XmN70uFgwex4rz7wRyI/sZgq3J3XaoERH6/xEkiGus6JERKrR1OUmc6aAPjrwBFdyfNTNSQ2/05n1Zd049yjvJ46/oOzxd3/eW31ERETKu33xDEb71vs6Tyy5d5Bn7r4QgJ2PPAyffm+ILRRH6XFPcpk+5/upp71b30/Skjq60j/eqUC3yUp7RZ2yOTvW9qq2awnnSwjyo4VfmHVO8bbPuLa7ffEMRp/6hr6smsy9dq1SJ4P7865yFCJSzujkNsBfB2TX2P6FFJqN0zz1HHeVphOJp8ntk6NuQugU6EpsuS96hvYM033ayQw99O0DtqvnIkkat+y0a2pewDjB8EX3bmdg7BZ15ohIKBpJVFZrZE9J0BrjJLGKW2dnmEnMRCQeFOhGbM7yFbE7+Yt4VauX3rmQ6By7G9DISyPSdp5wZrOw5IKomyIR69w9zujktobW+TcyYlhr/alGI/cb6cgUR3Xd5f68GOvvT9U5TETiL/2Ts2PqlJ8Ps2NtL9t61+jEX4eRjkztjSromDVLiZMkcdKWuEmdHuK4aM1235mN3d8BfgMuOZDXGrmrz81y7Oo7i/XovQqyUkIQVBNYpDUo0I3IT36/m+kLFzFz0eKom5IoToD67Q8ezfSFizh29Z3F27wGr90nnVwsGeFkDxYRkeZxB6f1BKr1BlxSXrWyh+XKgHXMmuVr/41WSgiayjyKtAZNXZZEca8L3da7pnhbtXU2fmt1SnVarxac4Y0byM6fG3UzItE2ZUosLnglGk5wuq13DTMXLebp5x6suG3Q0/aVHMmfsf5+6Jl4m/N+JHFJhbsawOlHnhp1c0QkRBrRlUhsueIy/mvR++qawuT3AqXSlE8FbPXRBWLjnGlzXqcjx23aXxDmLF/B9IWLom6GJEDQ0/Y1mhecJC6pUE1gkdahQDdCfqf+pIkzkhPliI4TsDnT5pKwzmts7xjZbA9dU9uiboo0YOvQQDF49SJu0/5EmsX5O0lLB0/SbOtdU/E85eW9ueqx61nXtz6s5omIVKVAN0JJm+4TpnoSQwTVUeCMLCVhnVfHQR1klmbobO+MuinSIAWsIvtVmmETh07RtHOC0aseu/6A+2YuWsz0hYvK5sLw8t5UGjVN0+wUEYkvrdGVWHDq7Lk5NVidn0vV6igoli8BOP+wqtu28uh6MzjrMdumTEnkmq4obRrcTPpLukurcs69WhIRjU2Dmz1N5fWTEdvN+R4f7Wijc2x8wn1+Oy/03SEifinQlaZwBzpeNVrM3c+XaD1fnq2U0MS5WKm3LJO7XrRKannnJE35TNQNEQmJzgXRCnu9cjGB5JnHFROPPbPkwrr2FUYdXuXqEEk3BbrSFO5Ap1nCyurqBLjlRqHTqtFOB8hf0Dqj7DvW9tI2ZUoipotHSclSRILldB6t61tPT3t33SOVQXrbV2+l/XWvY89vfsPOqBsTAud7Mo4zp1rlO1ykVSnQlaZxB7lOEHr7uVlGH/ocAI8OPFH3RUe5Xll3+Qr4cV37LaeVAly3IHq+Wz2pknORDWiUViQC7s6joT3DsSg/1/6610EmQ3suB4NDTXnOKGYkafReRJpNga5EYs7yFexev47RST8q3tbI6FWtL+xGp946Wq3+nvN6Gxn50NSw/TRCKxIv5WrEppm7s62nvTuS77F6ljKJiNRDga7EWlBBUhDT04Y3biibtMOZjpvGqbhB1BtsxdFvL0Y6MnSN5aJuhogkRBDLf0pHtBtRb5LBOctXFNfrQjAdqiIi5SjQlViLU5BU2vO/rm896/rW8xmVv5A6rD43yz9M+0DUzRBpWUvuHWTHWG/NrPxxEUYypkZq3DoB685HHmZg5S11dfZ6zfocZn4Hd4WGtilTyN51R2D7TrOuqW10tncyumeUkZ3jtR+QYjoW8aU6upJ6cUyAIenQ6Pq+WhetjU61F5GJ3H9TzoyKzt3jB9wnzVFv1ucg11a3eu6IenW2d5JZmqGzvTPqpkROxyK+FOhKpNwXFmFdZDTaA75pcHNALYknZ51UM9ZLuZ/D/XMcEsLUY6y/P9T9LzvtGhbMnhfqc4i0EudvauWZNxZvu2jNdhbMnhfrabNbrriMHWt72XLFZaE9RyPl46YvXORrlNVvB/Sc5Ss48tK/5NjVdzJn+YrQz70ikg6auiyRci4sGi1dE6atQwN0f+m2fE+va4rbgtnzOOeN83nm7guja1wAStdLNfO5nMyfYUzJi5sgO0yaXaoraElvv0izjYe8RMb5PmsW99+/12SRzmOcqcY7H3k4dXkxRCRYGtEV8aDcxUWasgk3c3q3+7nqnbYWB35HWIJ8rQMrbwl1ZCdsGo0RiZcovs8eeO5B1vWt5/QjT+UTx1/geUTdHfQndTaQiDRH5CO6xpj7gKOBfcAw8JfW2ieNMccCXwdmANuBC6y1zxYeU/E+kaDUqnlab6KsTYObeefvnlBcyxGH5AXNHF1znstdqulKjm/a89erdBTS6whLWPUqtZZMJDhp6risR73nqEY6SZ0RZL8jye5sz15mA0VRM1hE4iEOI7ofsdaeYK09CbgZ+Frh9q8CK621xwIrgVWux1S7TxKolS4ytg4NFBMXKHkBnLRxBzvW9rKtd03UTamq3lFI90huM9aki4h/CoQqqxbMRrEEwVkTDHiaVeOcg53lI865V+dgkfSLfETXWrvT9etUYJ8x5jDgD4D3FG7/FnCrMSYLZCrdZ60dbFKzJWBxvMhwrx+GuwPZpzOKeeEp7wtkf0m27LRr8muzz5zftDXC9QhiNMBdJ3LlmTf62udRPUcWRzDSwL2+7vAPfyTq5kjCKat+47yujQ1DI53cftctbx0a4ITscfu/e2KaF0REghN5oAtgjFkNzCcfxP4x8AbgBWvtOIC1dtwYM1C4PVPlvsGS/R4KHOq+bdWqVUfMnTs33BdUhdekC5JO1eoESjw5F0fV1ApcS+tE+gmcT8geB64kXs8sudDzY+PIfXGqhFTSqEY+Q+4psK3CuQZxfj79yFMjDfii6uR2B9hv++qttL/udQDs+c1vImmPiIQjFoGutXYJgDHmw8BNwBcD2vXlwLXuG1atWsXcuXOZNq2r4oOy2Z6Anv5A/7z4Jr6z+X7+/Lj3hvYcSdFPuMc6KJ2BpSBVAAAgAElEQVQvHVL2dqftz5S5za96HtesxwTx2Eo6XzqEbLaH3V2HxPazUK6NP9365IRtduzbXrb9Vz/+d+wc20WGDDlyTO2YUvV1VrvPef4gPm9RqtX+Zv4NSf2adbxLPy9TO6awc2xXzb+lapy/6exdd9D/rW8z67wPBNPYAHh5TY0c+39efBNA8TrkO5vvD+S9bPY5fHfXIexw/V7tuZ332/kfYF72Ha4teiCTAaA9l6u5PzlQ3K4tohT31xP39gUtFoGuw1p7lzHmNmAr8HpjTFthxLYNOBJ4nvyIbqX7Sn0ZuNN9w8UXX/xW4J6XXx5h7959Bzwgm+1hcHAosNdUbqRndOTVQJ8jyZJwHEZHXi17e7m21/t6aj2u3InJ73M1+tkO471y/hbGZxwe28+C08aRkVf5+JrPHpCg7PbFMxj9xQP84NlHJmQNzWZ72Lcvf47pbu8qjpyUvk73e1vtGJQ7RnE9Zl4NDg4d8Nmu5zUFfd6W6qI63oODQ9zwzi8Up53W24bpk2YUHzsSg+/jWueAbLZnwuhzuW28LIdwb+Mcg6CuR5p9Dh+fcfiE3ys9t7Ns5AfPPsLpR55a8fiWcm+ncmjlef3uqrWPqP/+ghDEsWiG0uPdCkFvpIGuMaYbmGatfb7w+0JgB/Bb4EngPOCbhf83OmtwjTEV73Oz1r4CvFJy81HhvJryJtRgJT9Vik9rNLfVOF+2GSAXdWNixJk+5uUiIg4XG+6p5yMdGbrGcpCpnNPPvRYsv9a7flG/9iBsGtzM5KgbIS0vjjkhaqlV79zLEgv3NkEfg2afn/w+3/CeYdb1rWdd33p62rs9lzJycgq0TZmimr0iCRT1iG4XcI8xpgsYJx/kLrTW5owxlwBfN8ZcA7wMXOB6XLX7YsedKGF8166WyjCcFtWSAXlZ5+UESDlgwex5YTQxkbxebFW72Oia2kZne2dDZZrqSTi1+twsS4fewU0LFiuxiUdbhwY4JupGiLikIZmVu1RbuQBu0+BmvmXvrbpNWi077Ro2DW7mtqe+UbzNT64MvwmvRCReIg10rbUvAadWuO9p4BS/98WJ8+VTWoM1ib3JYeg6ejYHTh6PJ6c3vaf9qQOSidXqaVdB+8ZVu9hwSjXlrs0xQn1ThmqNhjiBNucfVtf+obVKaIkkRRpmSpQmu3Nz14OvtE0aVOus1DVX8DYNbi5Z5ywST1GP6KZaUF8oM7ramNSZr7W6b3SU7SP1jVrFzYxTT4n1WoZyKpUlKDcqUAyOoKEASaJXqzffSxCriy0R/1oxM3Il9Yw+l16HpLXig5ep23EUhyU59XDXh08D5zo7TdfYkuc50DXGHAvMA/4QmAXMBHazfz3tw8BD1tqxENoZK0HU1fRjUmdnMSPgpFwORpIVHKZNuaCm3BeVpjrFX60pfZVmZZRq5vlAF/7SSuYsX5HYYCBo7mNQzzFZMHteKpdYPHF8Fz/pWw+QuNc31t+vz3YMONfZusZOn5qBrjHmg8CngHcVbsqU2eyPgCuAV4wxdwK3WGv7Ampj7HjtOXTXq5P0SGKvsZS3dWig6rS/OP79OlPldz7yMM8suTARSVLc0ydrdRqIlCoNBLQMYH+AtGlwc/Fao57R2jQcy1OfGmHGwkWJC3JFJHwVA11jzBnAcuAE8pmLvw78F/DfwIvkE0dNBmYAbyK/1nY+8FfAp4wxK4C/t9a27LCWkwQBbo66KdKAoC8E0nBhIXlephKG9X4nKUlKHDsMJLnU2bjf1qGBiktqgJpBsI6liKRZtRHdHwL/A3wA+J61tlwx0aHCvz7g34HrjDHHkM+K/GlgGPjbIBucNCdkj5tQ8F6Sx7kQaCQ7Z+fucUYnt9HT3q0LixgIavmBlylner9FJCju3A87H3m4ZrnCIEucxVmtDkX3DLu4rFN23sudjzwc+1k5IklVLdB9n7V2jd8dWmufBf7aGHMTMLvehsVVaRp/53c/ddkkmRpZR3PRmu08e/X5iZta1ciUuDhLSuKSSqWT0lASRUT8c8/g+OofHcxo33oeHXiC048sW8BigrTNJnLnK6h1Pq826h22ch2rmwY3MzlBs3LcnOveC095X9RNaYg70aukV8VAt54gt+TxL5Kf4pwqpev5qq3vc7hrsCqBjCRJlBcHXgxv3EB2/lzP27vXinq9OIxSpdJJSl4iIqOT2wDvSwOS0LnnRxISlVUaDElyTfG0LEVxJ3oll4u2MRIalRdqgNf6qM6UlGq1ViV91MERvrH+fl/b+60nqYRyIiLxFecgF6oPhiiDvkj4Gg50jTFZ4I1Av7X2N403KTnG+vuhJ+pWSFyVdnAMD26OuEXJFdYFwbpCSYpKnBFtuDvQ5xURCVLapiWnWXEJ3LkzuXL7GbEeAHHPgupp7+YLXedE3CIRfzwFusaYjwDbrLUPlNy+FLgamFT4/U7gImvtvoDbKZJ4SZ02FocLqDCnqGWAHJUTlMTh9afJSEeGrrGcRjFEApTU75dmisO5fHjjhgmjvHHPt+Aeif7Av/6KgbFb4PzDImyRiD+Tam1gjDHA14C3ldx+FvBF4AXgy8AG4EJgSeCtjKEl9w6yY21v1M0QCV1cLqDCCHIXzJ7HrWfeyILZ8yomk4vL60+L1edmmb5wkbKMitShng6iOAR4cRCHc3npcpu4T7126xrLr2Pt3D1eY0uR+PAyovvWwv+lUd0lwKvAXGttnzHmYGATcBFwW3BNjIfSrHnOH7wfce+5E0mCMEZ2dSEoIkngXhIDP/b0mDgEeK1uyb2DPHP3hflfEj4ietGa7ez+0pVRN0NSyBiTIR9f/gXwe0CXtbajcN+JwMeAWwoVfjypOaILHFH4//+V3H468Ii1tg/AWvsa+YVsc7w+eZJsHRooe7vTs+Wl/EqSeu4kOOrgCJbfBFSbPKyN1oVgc+lvQkRaST2DI3Ez0pHPUOylnJOIX4UB0x8AtwJvJj+YerBrk18DnyAfBHtWcUTXGLOP/NI1yC9jeyU/i3mC+cYY9xyGDJAr3JYBctbaNj8NSpqk1keV5lEHR3C2XHEZ47t25ZcNZDL5kgBLLqi4fa06115Hct0ZtKVx+psQkSTwmgixXK3ctFl9bpalQ++IdfIsSbQrgXnA3wLXk18e+0XnTmvty8aYR4GzgOu87rRaHV0nwdRngOVA1lq7o3DbYuC7wJ9Ya+93HmOMuRD4srX2UK8NSColVBFpvgnBpoe6d7XqXHu9MJmzfIWvqYJS24yutnwdw7GxqJsiIlKWc+53grvSpTPDGzfwdyMPTMhMXCnfg4hU9SHgx9baawGMMeUu8p4DFvrZqZc1us+QH539GHCzqzF7gUdLtj2afHKqVHFGhdb1rS9maP32B4/myu3Hq2yMiEgdJnV27h+VFxFJgLH+/gmB7lh/P0M9leuzO7XYRzva6BzLT4DsHMsx2pEpLnlzZipBfgQ5zon6tOxEQvRG8tOWq9kBzPCzUy+B7n8AW4BlxpgzgKnAO4E7rLU7S7b9Y/LZl1PFfeLKkc/Ues4b5zO8Mf9S0z5dRUTE4VyUxf2CTCTtnCDKS44QqV8jwZ1Ti/3EW/PL27b1ruGmBYsnTHV2z1SK2xIZ5zPm/KxlJxKiMfIxZjWzgFf87LRmoGut3WuM+XPgG8DZ5Edyvw18xr2dMeYd5EsQLfPTgCRy1vXpD14kOZyOqbTwunYsaM6FWNwuyERaScesWSw7aTEPPPegcoSErPukkyeMuu585OGGO/mSMkDiBOr6jEkTPAm8xxjTbq3dU3qnMWYKMB94ws9OvWRdxlq70Vp7PHAY0GOtPc9aW7ro7Zfkpy5/z08DolTvhW9STlAist9Yf/+EkY+kj4LMWb5C9WhFWpQ62purdNS13uvHJE79DaL8Xto6mpOka2ob2WwPXVNjnxt4NfA7wNeNMRMu0ApB7teA6cAqPzv1MnW5yFq7rcp9O4HSqcyxVrrWQkTizZ39uG3KFKa++wxfj3eShNTbQ106jUtERFqPn+tHd6AYt2tO9xTqSpmjgxjc0fV2dDrbO8kszZC7Nt75MKy1/2KMmQ98GPhT4GUAY8wTwPHAZGCVOwmyF74C3bRqhbTwImlQmgEznwm5tlN+PsyOzb0ADZVGUDZNEYmTIEbbJFxxvr7cOjTAt+y9yhotsWCt/UihhNBngLcUbn47YIHl1trb/e6zWh3d91trv1tXS/OPfx0w21oby3ocz/7jMl7b9Ev+4eDHi9nvKv1xaxRHJJ68TgP7ye93s+Do9xSDXF0cikgaxDmISrviut3zD4u6KXVxKopkom6IiIu1djWwujB9eTqws0zyY8+qjeh+xxizEbgRuM9a+6qXHRpjDHAJ8AnyialiGej6ocX4IvFU71SotFwcJnG9123zr+PQaT1RN0NEpCHNSshXWrs3KM4ATg5YeeaNoVznVkriFdZrkvQo5IIqzQflW7VA94+AfwS+Bew0xvQC/wX8DPgN+bnTHeTrGb0JOBU4C3gr8BrwFeDLjTYwLMf81VW8+G//xk0LlLVQJEmSGNyFpdkXCpsGNzO5wX0cOu1w1c8VkdTo3D3O6OR8op8wZv2Ftb61GeWpKpVO0ppdaZaKga619mFjzEnAecClwAXkFwhXkiFf2+grwAprbV+A7YycpjqKxIO+HJvPmeIGJXXlRERagDsRYqa9nR1re8kccgi5V1/lkh++xtOfPiuUARNnRLRSSaNGcswEPVvRa1u29a5hx9p8zozskgsCeW5JB2PMycDngBOBo4CDy2yWs9Ye4nWfVZNRWWtzwN3A3YUpyfOA08gX7J0B7AZ+C/wc+BHwkLV2t9cnjwsvQWxapjqKSH1aeSTZCXJFRFqRE2Q6yRBL/x8e3Fz3vkurCbjVqlu+dWigruvTMJKwem2LkyujkcSQkj7GmHOB75AvfbuVfGy5t9H9es66bK215LNerWz0SePCuXBVECsitcR1JNnp8W+bMkU1dUVEmqC047OR68g5y1f4XrPaSKDqzNDpae/mPHNu8fZGZi5e+tDnAHh04ImqWZsbDbA3DW6m+0u3Fb/zhj//CV3Dp8dSYBT4E2vtj4LaaUuXF4rrhauIiFe1evxFRCRYzvVjUDN9/FyPurMl56gdXJZyZugM7RmeECQGETDWmv1T7wi0+/HHuL7zGt2fxMrvAt8IMsiFFg90RSTd3Mk2WnnqsYiIBK/ZAybDGzdMyJYM+4PLOGYyrjQtu57vYyfAd/JE3L54BqN961nXt171f9Pht4CnCj9+KNAVkdRSaTAREUmLsf5+KKnOdtG923nm7gsBYreExb22+eYZTzHUt973CLSjdLTYyXRd7j5JpO8CC4wxB1trXwtqp5OC2pGIiKTfSEcGODBpioiINNeC2fPoHBsv/p7kJSzDGzd42s75Duoc21+iLswSSdI015Cvm/uvxpjXB7VTjeiKSKqpNFiwVp+bZenQO/KZRmM4VU5EROKlY9Yslp20+IAZVj/d+iRHHzIH8F5b1/kOumnBgfuT5LLWjhhjPgo8AvQbY7YBO8tsmrPWGq/7VaArIqmmRBXhcS5MagW8KxZcxxE9hzexZSIiwYtDrgd37gm/NjVQBsmLSm1yvh9KO577XtnK0YfPqVkvuBKvHdnqlI0/Y8w7gR8AXcC+wr/Jje5Xga5Ii5vR1cakzk72jY6yfWS89gNEYMKFydR3n1H1IuKInsPJLM1PN8tdm6u4nYhInDU7WHKSObmXirhzTzzw3IO+9rd1aCDoJgKw8swbPY2uVup4rlU9oNK05lod2c73FMRv/bIc4B+AQ4CPAd+01jZcQxcU6Iq0vEmdnZDJMCmXg5GhqJsjCaGyRiIi4ZqzfAXbetcwc9HisvfXszSnkRHhID3w3IOs61vPd3/xQDGTcil3oMr5hxVv9zqy7v5+0ndV7J0EfMtae2eQO/Ud6BpjFgJ/Afwe0GWt/d3C7b8HLAT+xVr7QpCNTJOuqW10tncyumeUkZ3pHj1zRgoBjRaKRKQZU7Z2rO1lx9pe9ZiLSCpFeT3TMWsW23rXsGNt7/4bj+8C8iOaz3jcj1Oep6e9m5Vn3hh8Q306543z6ew6hDMOfzdb7r/sgJFrqBycahpyKg0D24PeqedA1xiTAe4EPlS4aTcT506/DNwAZMgPP0sZne2dZJZmyF2bY4R0j545I4WARgtFIuKso900uDn09crqMReRNIryeqb7pJPpPulkZi5avH901+eUZdhfgieOpXjmLF+hdbRN4u604dVX4ZBDom3Qfv8OnB70Tv2UF/oU8GHgDmA6cLP7Tmvti8B/AecE1joREQlEI2uz3FPcetq7Y5GQRUSkVcWxmkA9bZp96FHFn8sFue4RXqecUCNTrsNOxpUExU6bTCZOQS7A3wDTjTErjDENJ6Fy+Jm6/HFgE3CRtTZnjCmXUeRZ4KxAWiYiIqHw23O+7LRrAFTKQUQkBuJYTaCeNr39qBMZHKw8Ou4shdnWuyaQckJbhwY4IXscwxs3kJ0/t+79SCjuIj87+FLgI8aYp6lcXshzrOkn0DXAKmtttZSZvwWyPvYpIiIhcWdG5tPvnXCb1tOKiCSfk5nZ+bmSuCShakRQI9lj/f2B7EcCNc/1cw/wtgrb+Srd4CfQ3Qt01Njm9eQXE4uISMTKZUb2my250tpe98WViIiEr9yykVodls453JmZk2SNjGTfvngGo33ref3yb9M5Ng5LLgiwZRKAg8PYqZ9A95fAXGNMptyorjGmAzgT2BhU40REpHHOF/y6vvUVyzhU4kz1KuUkDxlYeUswjRQRkarqSdZU6RzeCtwdsqOT2wDyQW4AJiR1GhsLZJ+tzFobSipzP8mo7gLeBPyjMWbC44wxbcBy4EjymZlFRKQJnKlq1aasOV/wpYY3bpjwfy2l08a8XHQp+YeIiERhzvIVHLv6To5dfWfg+56Q1Kmj1oTX6I3tbc1g3M+I7irgT4DLgD+DfG0cY8x3gVPJB7m91tp/CbqRIiJS3ttXrWRSZ2ddtR3H+vt56a6ve16z63dUwKnbOO/N7/D1OBEREQlOx0EdxfKmcWSMeafXba21j3vd1nOga60dN8a8F/gC8GngdYW7zgVeAf628E9ERJrE6VWut7aj3zW7pbwmQhERkeZyOhvX9a2np707Fet06+Uk40ojZxp1PR3eMfIY3hNNlZ+mVoafEV2stXuB64wxS4FjgRnkUz8/HdbcahERiYZzkfTowBMVL5DmLF/Btt41zFy0+ID7lp12DQ8892DYzRQREalq//fR3VE3JXCNdnjHxA2UD3QPJZ+B+e3A/eRL3XrmOdA1xswCXrHW7ioko7JltukBpllrlbdbRCQBnBFZjcaKiKSLE9wlvf55uWzT9VLFgHiy1n6h2v3GmCXk80Fd5We/fpJR/QpqJuy8rLCdSFUzutom/C8i0ZizfAXTFy4quz532WnXsGD2vJae7iYiItGqJ9t0JXOWr+DIS/8ysP15oaSMjbPWrgZ+Sn7k1zM/U5czhX8iDUvJNIvU65raRmd7J6N7RhnZqdUJaTDSkaFrLAeZDDvW9rLzkYeZ+u4zom6WiIhIUwQZOHuxdWiA7i/d5jnxo1S0EVji5wF+RnS9OAIYCXifIhKRzvZOMkszdLZ3Rt0UCcjqc7NMX7gIcvmlMJrCJSIiEq5GEz8KAEcBB/t5QNURXWPMBSU3nVjmNshnv5oFfAh4yk8DREQkXJ27x4u1dHvauyNujYiISPOV1oJvBiepY621n1KZMSYDfAR4P+C5tBDUnrp8J/szYOWARYV/pZwpzaPAUj8NEJE6jI2RzfYAJD2dvDTBRWu28+zV5xcTkmzrXeP5sVFcGIiIxIFTtiXJdA7fz28t+CCktaRR0Iwxz1S46yDyJW3bgdeA/+Vnv7UC3Y8W/s8AXwPuA3rLbDcObAd+bK19xU8DRKQOHR2QyfcvaZ2zhCmKCwMRkThw8ok4Sz2SSOdwSYhOypcX2ke+0s9Pga9Ya3/hZ6dVA11r7dedn40xHwHus9Z+w88TVGOMmQHcBcwB9gDPAhdbaweNMTny06D3FTb/sLX2qcLjFgI3Fdq/AfiotXY0qHaJiKRNmL36QZZ+EBERkdZirT0qjP16zrpsrQ0jLWcOuNFa+yMAY8xNwDLg44X732mtnTDmb4zpBm4HTrfWPmuMWQ1cCVwfQvtERFKhtFffXT+30UC1WgZLTZsTERGRKPgpLwSAMaYTOBc4CTgU2An8D7DGWusr47K1dgfwI9dNTwCfrPGws4GfWWufLfz+VeDrKNAVEfFszvIVbOtdw8xFi0N9Hk2bExGRpFKZxWTzFegaYxaQDyqnM7Gmbg74R2PMR62199fTEGPMJPJB7vdcN//IGHMQ8H3gOmvtq+SzO//atU0/8IYK+zyUfDBetGrVqiPmzp1bTxNFpEU5CUmSlvjLPWorIiIi/jhlFnPX5hghmHwowxs3NL2Wb9wYY66u86E5a+2XvG7sOdA1xvwBcC/5UkL/AjwE/IZ8JqwzgfOA7xpj3mWt3eCryXm3AMPArYXfZ1lrnzfGTCG/jveLwBd87vNy4Fr3DatWrWLu3LlMm9ZV8UFONtuw1fs8zWpf0Cq1O6mvJ0iNHgOvj6+1XbX7k/A+hdrGTIZJuRxZHwk4/ban0eNfuk32rjvo/9a3mXXeBybcvrvrELLZnuL/cdJq58Wk0vEOh74n46GR78pW1MjxiNuxDPp7eGrHFHaOTayd27b9pdBed9yOZxV/V+fjckDwgS75dM458mtjnyi5705jzEry05CvBt7nY78YY24GjgEWWmv3AVhrny/8v6uwDveKwub9gHu98Czg+Qq7/jL5EklFF1988VuBe15+eYS9e/cd8IBstofBwfAy2Lo/gF6fp/RDG2b7glSt3fUchzTx+57WOnF5OYaVPtvV3oskvE/NaGO9f7de35dK+/byvLW2GZ9x+AG3j4y8yuDgUNn7wuDni7ee9oR93paJdLyDVetvWMc7XOXOT87xrnTu0vsRzHdvlJ9tr+9tpdfp9fE3vPMLPPDcg8Ddxduc7+CgeL2OiJn3NONJ/AS6pwP3lAlyAbDW/sQY813gLD8NMMbcAJwMnFOYmowxZhowZq3dXZi6/H7gycJD/h241RhzTGGd7iXAdyq06RWgtNxRKFm9RETiqNr0qFafOiUiIhI2JWU8kLX2h814nkk+tp1K5ZFTRz/geTGYMeYtwOeBI4HHjTFPGmPWAG8CfmKM2QT8nHyB4C8CWGuHgE8A9xtj/l+hXTf7eB0iIi1N5YBERESaQ0kZo+NnRHcAeHuNbd5Kft2uJ4Wiv5kKd/9+lcf1Ar1en0dERPbTSK6IiEjzOMkhyWTYsbaXnY88zJzlK6JuVuwYY14PfJgDq/t801q71e/+/IzorgPONMZcZYxpK2nUJGPMXwPzCtuJiIiIiIi0vDnLVzB94SLI5QDyQa9MYIz5GPAs8PfAn5Ffx/t+4AbgWWPMEr/79DOi+7fAnxae/GJjzKPkR2+PAE4DZgMvUn8WLRERERERkdTpmDVLZf8qMMacAdwOjJBPJlxa3efTwFeNMVustQ973a/nQNda+6Ix5l3AKvIR9u+UbPIfwCXWWs9Tl0VEREREROKu0fq33SedTPdJJ6uObnmfI19m9m3W2mdct/8CWG+MuQP4GfBZwHOg62fqMtbaPmvtWcAbgD8hP4f6T4A3WGvPstb+ys/+RERERERE4m6svz+Q/biD3OGNGwLZZwq8HfhOSZBbVKi0cw9wip+d+pm67H6yF4AX6nmsiIiIiIhIqxvr79fobl4nMFhjm98WtvOsrkBXRERERESkVQSZLXlb7xp2rN1fQKZj1qxWD3ifB86osc27qV3qdgLPga4x5mseN81Zaz/upxEiIiIiIiJxFlS25JmLFjNz0WK29a4p/h/nQNcYczPwPvLJh4+31m4us811wKfIl6QF+C9r7aUen2INcKUx5hbgf1lriwfaGNMNXA+cCtzsp91+RnQvrHF/jnxN3BygQFdERERERFJleOMGsvPnRt2MZrsP+ArwaI3tvmGtvbKO/d9APu/Tp4APGWM2sr+6j1NT99nCdp75SUZ1dIV/JwGfALYC3wbe6KcBIiIiIiIiSRBUUiqHM415W++aQPcbJGvtY9ZaX9OGfe5/J/BO4E7gEGAucB756cyTgTuAdxS288xPeaFfV7jr18AmY8wPgJ8D64F/9tMIERERERGRWMtk8mtrl1wQ2C5nLlo84f9m+/73v3/E5ZdfPrvk5lesta/UsbsPGmPmAy8C11prf1xpQ2PMImCttXYfgLX2ZeDjxphPAm8GpgI7gf9rrX21jrYEl4zKWvu8MWYt8BkSEOhOm9ZV8b5stqcpbaj3eZrVvqBVandSX0+QGj0GXh9fa7tq9yfhfWpGG/08h9/2NHr8k/Ae1dJq58Wk0vEOh74n46GR78pW1MjxiNuxrNaed/X+W0OPL7t9IWDOBhQ413M8b7rppnvK3LwUuM7nrr4K/L219jVjzHuAXmPM71lrt1fYfg3wQqFG7j87g6rW2j3Akz6fu6ygsy6/BBwT8D5D8fLLI+zdu++A27PZHgYHh0J7XvcH0OvzlH5ow2xfkKq1u57jkCZ+39NaJy4vx7DSZ7vae5GE96kZbaz379br+1Jp316eN2nvUS31vIawz9sykY53sGr9Det4h6vc+ck53pXOXXo/gvnuifKz7fW9dW/3qwd/xMDKW4DKQa/f1zO8cQPdJ51cTEpVD6/XEZV89rOf/bPLL7/8ZyU3+x7Ntda+6Pr5P4wxzwPHAY9UeMh64I+ALwBXG2P+A7gN+J61dtzv85cTWKBrjGkDziQ/xCwiIiIiIlXM6GpjUme+NOi+0VG2jwRyfS8hCCMrsrPPjlmzAt+3V2efffaLZ599dl+j+zHGvN5a+0Lh5xPJZ2i2lba31gHfn54AACAASURBVM43xvwOsIR80uOzgPnAbwujvKuttc810iY/5YX+sMo+3gB8FDgRWN1Ig0REREREWsGkzk7IZPI/53IwotHiVhTn0kIAxpgVwLnksyCvN8Zst9a+xRizDrjGWvsz4AZjzMnAOLAH+LB7lLecwnTlLxpjrgUWABcBZwNXAZ8zxjxEfpT3PmvtXr/t9jOi+yPypYMqyQD/CXzWbyNERERERESkvE2Dmzkhe1wkz22tvQy4rMztC1w/f6SB/e8D7gfuN8YcAXyMfLnaeeSnN28zxtxJfpT3Wa/79RPoXk/5QHcf8DLwU2vtT33sT0REpCJnSp+m84mISBy0TZnC+K5dkTz31qGByALdZiqMAt9AfoT4j8hPbf5T4Ergr/ERv/opL3Sdv2ZKVWNjZLM9uoATEanAmdKn6XwiIhIHc5aviHW92xR6BJgOHA283e+Dg866LF51dOgCTiRkXVPb6GzvZHTPKCM71aEkIiIiybHlissY37WL28/NMtqR4dGBJzjPnJv6kV1jjCE/knsBMJP8Etk+fOaC8hXoGmPeDvwhcBTQAQwCG4B/t9aO+dmXiEjYOts7ySzNkLs2xwjqUBIREZHGNDNDsjNNerQjn7BsaM8wtz31DQB62rtZdto1TWtL2IwxHcCfkw9w30U+uH0NuBe43Vr7oN99egp0jTFvI18E+MTCTZnC/86a3R3GmM9Za+8oedxB9WTIEhERERERiZu4ZEge2jPM8MYNZOfPjbopDSmUIroIOA+YSj7O3EJ+9PYOa+1v6913zUDXGHMO8G9AO/Ab4GHg+cLdbwDmAkcCq40xx1hrry48bj7w+8DN9TZOREREREREDjTW3x91E+pmjLmE/OjtSeSD2z3APcBt1tqHgniOqoGuMeZw4FvkMyt/knxK5/GSbSaRT//8ZeBvjDH/AfQA3wa+FEQjRUREREREWlHn7nFGJ7eRYf902ovu3c6OsV5YckGUTWvEPxX+fwa4Hfi6tXZbkE9Qa0T3r4Bu4H3W2rIpxgp1j243xgySn0N9F5AFtgFKSyYiIiIiIlKni9ZsZ/eXruSE7HE88NyDnPPG+Wy5/zLGx6IpdRSQu8mvvX0krCeYVOP+PwZ+UinIdbPW3gf8hPw05v8LnGKtfarxJoqk29jefKmprqltUTdFRERERGKoNNPynOUrmL5wUUStaZy19kNhBrlQO9A9Gnjcx/4eJz+i/i5r7da6WyXSQjoO6iCzNENne2fUTRERERGRmGibMmXC/6WamQE6iWpNXT6Y/MJgr14DXrXWjtTfJBERCcKMrjYmdXayb3SU7SOqIywiIpIkc5avYFvvGmYuWlz2/rhkgI6rWiO6vwGO97G/txQeIyIiEZvU2QmZTP5/ERERSbyjeo6MugmJUSvQ/U/gPcaYN9XakTHm94CzgFDnWreSrqltZLM9UTdDROuIRURERCJQOj25dK2uVFYr0L2V/PTl+40xb660USHIXQu0ASuDa15r62zvJLM0E3UzROpeR+x01ihAFhEREfFP05PrV3WNrrV2gzHmJuCzwP8YY+4Ffgg8X9jkDcA8YDHQDtxord0QYntFJEGczprctTlGGIq6OSIiIhIgZ8YXwOieUUZ2Kh+ExEetZFRYa//GGDMCfAH4IPCBkk0ywF7gOmvt9cE3UURERERE4saZ8QWoU1tip2agC2Ctvd4Y83XgY8C7gNcV7noReAy4w1rbF0oLpWFO5lVA2VdFWpwyMYuIiEgr8BToAlhrfw1cG2JbJCRO5lWASbkcjKi3TaRVFTMx61wgIiIiKeY50BURERGRdOia2kZne6fWVYpIatXKuiwiIiIiMTCjK5/JPpvtYUZXY9nsnWSBfrPpi4gkhQJdERERkQQoLkXKZIq5N0REpDwFutIcY2OB9ECLiIiIiIjUojW60hwdHUqAIyIiIiJNoaojokA3xZxEEyIi2WxP1E0QkTq5L9hFxBtVHRFNXU4xJ9GEiEhmaUbnA5GEcl+wi4iINwp0RUREREREJFU0dVlEJO4KydxA64xERFqN1pqK1EeBrohI3BWSuYHWGYk0wp27YnTPKCM7FTBI/GmtqUh9NHVZJAWy2R66pqp0k4hINU7uiszSjJI1ioiknAJdkRTQRZuI1GtGV5vqnIuISOoo0BUREWlhzrRIla8REZE00RpdERERkRbgXqMsIpJ2CnRFREREWoCzRhkgd20u4tZEwwn2lYxMJP00dVlEREREWoIT7GtkWyT9NKKbUOqRDJ/KUIiIiIikQzbbo+u5FqMR3YRyeiQnTZpENtuj8jIhUBkKERERkXSI4nqua2pbQ9foyorfGAW6CddxUIeCMRERERGRWsbGyGZ7mvZ0jU6VV1b8xmjqsoiIiIiIpF9HB2QykKsvGduMrjYFnQmiEV0RERERaSlje5s7sifp4IywSjJEOqJrjJkB3AXMAfYAzwIXW2sHjTGnAquAyUAf8CFr7W8Lj6t4n4js5/Q87hsdjbopIiIiseEs/WrVMkvN4B793Dc6yvYRJYGS5op6RDcH3GitNdba44EtwDJjzCTgm8Cl1tpjgf8ElgFUu09EJtLaDhERkQAV1ngqOVBtxdFPXYdIRCId0bXW7gB+5LrpCeCTwMnAmLX2scLtXyU/cvuxGvdNYIw5FDjUfduqVauOmDt3blAvIfHU2yYiIiLiUWGN56RcDkaGQn2qRteDqkyitLrYJKMqjNR+EvgeMAv4tXOftXabMWaSMWZ6tfsKgbPb5cC17htWrVrF3LlzmTatq2Jbmr1mw+/zVdvey74O2Kaw1mBSLke2CR1upc+flDUyQbRzbO8YHQd1hPYctR7f6P1etwnycUE9R1DP72c/Qf5te9kurOdrpnpfWxxfSxI1+hlMmri9jqj+huN2HKIW5d9B2Wu0ksRJfp43szR/jZe7NkdntuHm1eT3ezhun73Ar7EdTrbnsbF8Z0nAbfOzTSuJTaAL3AIMA7cCiwPa55eBO903XHzxxW8F7nn55RH27t13wAOy2R4GB8ProSv3Aaz0fJU+rIODQ1Xv8/L4StsE+dq9tj/M492IMI5NNttTdU2Q389Crcd7eQ3V3gs/n9dymvE+e23/4OBQ3b3b9bwOr+cSv8e/dLt6Hl9p+7D4+eL1+tpK9x/X80gS+P18J/l4h/mdV69ax7/a34/f9ns5p6Sdl/ORczyacQ6t9pls9P2K6hrP6/PXOpc0OuuwnqCv1nWE389EcXtXtuegr6MauQ5Iu1gEusaYm4FjgIXW2n3GmH7gd1z3zwT2WWt3VLuvdL/W2leAV0puPiqM1yAi8efUs4N87/YIrXNxJ5JWTgeWpmaKpIs7w3EzpopL+kSdjApjzA3k193+qbX21cLNG4DJxpjTCr9fAtzj4T4RkZYwo6ut5XtqRWB/B5YzW0NE4q9raj6ZVzbbU/xZJGhRlxd6C/B54BngcWMMwK+stYuNMR8GVhljOiiUEAIojPiWvU9EpFUUe7rrLHov4VOyPxGR8jTDSpoh6qzLvwDKVl221j4OHO/3PpFQFJII6GJVRLzStDsREZHoxGKNrkjsNbGcgEjcqESFiIiIJE3ka3TFJ3d68hbirEdUgXaR5nOmmGkdpIhIQeF6TNclLcK5/pZE0Yhu0rjSk7cSZwqgRlRF4kXrUEWkJWmmV2tp0evvpNOIroiI1K24DjWTKQa8IiIiIlHTiK5IC3FG31pu5K1Fp/yniTNlTGuERURExAsFuiItpGWngGvKUeKpDEW6aMq7iIiETYGuiIiINJVKL0mjWnaGkoh4pkBXIqcpiSIiIuJHnGYoJek6xikXl4S2ijRKyagkcipbIiIiIkkV5XWMU37Ra6kjp1ycrrmkFWhEV0REvCsk9tJ0QYmSe42vksxJLc4oZhppGYBIZQp0RWKseDGnC7nUmXChniSqHSkx4L64V5I5qcUZxYR8QjsRaQ2autyCstkeuqbWnt5STdfUtkD2I9UVL+Y6OqJuigRswoW6SMh0zhYRkVajQLcFNbI2w1kL0rlvktZ4SNM4nzsv64/C5qyFUsAgcedeuxeXc7bTJhERkbBp6nLUCuvdIBm1BIujUJoqJk0Up+yaqannqrW2qRfH6b2Nfoekea2liIgESyO6USusdyOTSeZ6PRFJJmetrc47kiDutZYiEi5nyYNmMUlSaUS3VblGkkUkQfS3C0ysBZkU2WyPr9qV7tHLtNe89HtsJE/HTcJUmsQr0bOYpCVpRLdVOSPJIpIs+tsFklkL0m97ndeYtNdZj1Z4jWHQcZNmc0Z5RZJAI7qSWu7yLVqHKHGg9YXBG9s7RsdBHWVHtlppRNQvfRZFpB5OB5zKNEkSKNCV1FIR9RgJKvFRwpK3lVItx+B1HNRRcWqdpt1V1qzPotPhmMS/VxERSTYFuhJbGnFIESfxUaMdDq5pu+q8aE1je7VGOUnilDG9Hu614JoRICKSLFqj65OzNqHVss9FsSbDvT5NUqIwIhtITVxndHdsLJi2SSK4R3BFwpbEteASP+6a1nGoBy/poLrk/7+9ew+W5KoLOP7dR5J9EDaSbAwQs7GUHCVGQggIiFQQRJSiSuVlJGARhISNpAAt/EMlQAmmECgKScwWjwIJD4kiohKxeKQwUNEUYTUR+ZGSvCwJbAIbkl03r73+0T03s7MzfadneqbP9Hw/VVv33pk+jz7de7p/3adPr81At6ZlPej5Sgc1osnXafXy2rSpmbrVVQbanrQslmW9WNm0Lr12xH1itN6JtP3cZHr71uqjVC2+0s3RMN1zyLvSNZSBriRNwvfQLqRlvVjZtC7NCL3o+0QvgJk0UK9Kvzr03H5uIjndJOjCaJhlvyC1ffvRPOyYjasXGbU2A11JrVn2g1YWvDM9lS7d2dRi6gUwkwbq06afN4drLq9F2k9nYd2b17H5iM0+1leDga5Ukye0zVn2g1YWlvTO9LR3wXq6dGdzpg44bHIZzWJYeFeGay5rwL663s6voTkw0NXSaOpgu5AntB5QpEOMcxfLCWQa1DdjejbqTGjnyIeJLPqw8FnqSsBe1+p6tzW/RoZ8Fn52DHQ1Uv+QvC5Y6oNtjieZC6CN2caVjxwmkNEM1ZnQbklHPmg2pj2uOLKsW3wWfnYMdDWSr/eZjneDFkPV0LqcJhLRdJxxVJqOwVVzpj2uNHHhvqnHNxrhiAnNiIGuNCPeDVoMDq1bDl2YcVRq0yL2k47KGS2rSciWcMRE/80QzY6BriRJOowzSmvROSpHueq/GaLZ2dh2BbTg+mbSPLh/P3fue7DlCkmSmtAfJKxctMI+7m65Rqpr67YNbDlyC/vv28++u5o9Ph+7dQPrt2zx2C8pW97R1XR6k3ks2ZATLT6f2dQiyep5ukE+X5etWT6a4QQ6knJnoCtpKfnMphZJ68/TVQWzGT9f52s7JGl5OXRZkjRUb9ijtBrMrqy0XZNaVu86rqzAPodeS2rZAUeTzZN3dKVlVHa0draq4kQu0mhVryabZllJHdZ75E9zsbSB7qatU656jWeSDplC/MCB6cpVI5Z+NtG+Z6vr6D0nuLTtJkmlOs+/+hozNa2peSY8rqvLljbQ3Xzk5ukyqPFM0iFTiG/aNF25OswkV8p7Jx2eeNTTe07QdpMkAU5G1pKm5pmY53G9yVFkS3/DQmNZ2kBXi63/LvmWg+sNvCRJakMGk5EZ7CyGJh+F8YaFxmGgO4b+q0bKw8R3yXuTADQ4hNxZPSW1yec/tewMdiQNY6A7hv6rRlpwvWdTGxxC7rsEpeF6AZhmq8vPf3ohsSP6JkB0W0qaFwPdBnglXdLSGeMVCV2btdm+fv5yvJDoCK8J9E2AmNO2VA0zGBEnzZqBbgO6eiVdmgsnMllMS/iKBPt6AY7w0nKawYg4adY2tl0BSUuuN5HJygrsu7vt2khSY47duqG4g+ldsMNs3baBLUduYf99+9l314NtV0dSB3lHV/KO4kR6795zKKcWme+Q1CytTpzoXbCHlMdc35igiTiEWjUY6EpzejVC157p6r17z5MUn91cZHXfIbn0F3h6J5eeZK5aqn2ib1KpiTkEVtNw/1ENBrrSnPhMV3cZ8C+Ppb/A40nmYZZqn+ibVEqScuczujPUe/5EzeranVF1l8+gSZIktcM7ujPUtVdr5MI21aLo8vtNNSHnBFhqPhMuSfPjHV1pAr2TFUnLaeI+wFnGl1pvmDPAykUr7GM++4DHLEnLyDu60gT6J7CR1uJJZvf0ByxS7txfJS0jA11JmjFPMiVJkubLQFeSJEmS1CnL+4zuvfeyffvRHNy/nzv3ORuqJGn+jt26YfUd3h6PJElqTuuBbkrpHcDzgZOB0yLihvLzm4ED5T+AP4iIz5XfPRnYBWwGbgbOiYjv1Sr4qKOcEESS1Kr1W7asvpN0nONR73lvX1mlZdJ/QUiSxpXD0OVPA08Hbhny3Qsi4vTyXy/IXQ9cDlwQEacAXwYunlttJUlqSe95b19ZpWWyekFonXMdSBpf64FuRFwdEbfVSPIE4EBEXF3+fRnwomnq4PvsJEmS5q83SsHzMElNaz3QXcNHU0r/kVK6NKV0TPnZSfTd/Y2IO4D1KaVHDCZOKR2TUjq5/99VV111wuByXh2XJEmaP0cpSJqV1p/RrfALEXFbSuko4N3Ae4FzaubxWuCi/g927drFWWedNXTh3nsuJ33fZRPvyZw2j0VIX7XMItTf9M2X21Q+pm83fQ51WKT0w5adR/pF7YPnsW7zXP9h79fOuf2XIX0T+bS9DsuaPodt34X0XZNtoNsbzhwR96aULgU+U351K7Cjt1xK6TjgYER8f0g27wY+1P/BeeeddyZwxbAy9+y5m+3bj2bPnkMnAxl3p5k03ag8upq+185tlb8o6SfJo430Bx44wKaNm4ZOjjNt+XXzyan9lmX7V+Vh+ur0w/rCuukHl8upD54kj6r0VfWeR/px1Enfu5O5ctHKyPR169B2H9B0+rr5NNGH9eeTex9i+uHpmip/kjwWPX3XZBnoppS2Ahsj4q6U0jrgN4Hd5ddfAzanlJ5WPqd7PiMC14jYC+wd+PjEGVVbWkr9J2v7cAZzSZIkta/1QDel9B7gN4ATgM+nlO4Engf8TUppA7AB+AawEyAiDqaUXgrsSiltony9UBt1lyRJkiTlp/VANyIuBC4c8tXjK9J8FThtZpWSJEmSJC2s3GddliRJkiSpltbv6EqSpJoO9M3Ye+BAu3WRJClDBrqSJC2aTZtg3bri95WV6mUlSVpCDl2WJEmSJHWKga4kSZIkqVMMdCVJkiRJnWKgK0mSJEnqFANdSZIkSVKnGOhKkiRJkjrFQFeSJEmS1CkGupIkSZKkTjHQlSRJkiR1ioGuJEmSJKlTDHQlSZIkSZ1ioCtJkiRJ6hQDXUmSJElSpxjoSpIkSZI6xUBXkiRJktQpBrqSJEmSpE4x0JUkSZIkdYqBriRJkiSpUwx0JUmSJEmdYqArSZIkSeoUA11JkiRJUqcY6EqSJEmSOsVAV5IkSZLUKQa6kiRJkqROMdCVJEmSJHXKxrYrIEmSJEnKV0rpFODDwLHAncDLIuLGgWU2AO8BngOsABdHxPvnXdce7+hKkiRJkqpcBlwSEacAlwC7hizzEuAngccATwHelFI6eW41HLCMd3SPWP1tx47ix7bi58aN6w/52a+3zCG/j0g/NN2O0en7vxvMY1j6wXL76zZO+onKH5JuWN6HtcGQeq8uM5jPGuVXlTtyG1Ss97C865Q/Tvph5Q9LX7UPjSx3nPXvX27Uz6r6j1nvWv8HKrbJ0PqPWo++3+uUP239q/aJuu03uE7j9iGjtuU4+0/d9OPUe5w+pCp9VR8wznYbtw8ZlW6c8ptMP6ovrFv/SfvA3jKT9oF1+tBh6ar6gqr0h9V72vRD1mUWfUjVsWPaPrBOHzZpH1517J22Dxur/MGyhpRbZ/2Hftaf92A+FceeWucxE56HjbPdJ+1D6vaho7bbpH3gpOdRYx07xkhf9zxo0j5snPR1juOTnkeM2t+/8IUvnLhz586TB5LtjYi9vT9SSscDZwC/VH70ceC9KaXtEbGnL92LgfdFxEFgT0rp08ALgT87fMVmb93Kykob5bbp1cClbVdCkiRJktp09tlnc9111w1+/OaIeFPvj5TSE4C/jIhT+z77BnBORFzX99n1wLkRcW359xuAEyPiwhmuwkjLeEf38vLnN4H726yIJEmSJLXgiNtvv/2Mbdu2fQ64Z+C7vcMSLJplDHTvBv6i7UpIkiRJUltOOOGEL1122WXjLHob8OiU0oaIeLCcdOpR5ef9bgV2ANeWf58E3NJUfetyMipJkiRJ0lAR8T1gN3B2+dHZwNcHns8FuAJ4ZUppfUppO/BrwF/Pr6aHMtCVJEmSJFU5H3hNSulbwGvKv0kpfTaldGa5zEeAbwM3AtcAb4mIm9qoLCznZFSSJEmSpA7zjq4kSZIkqVMMdCVJkiRJnWKgK0mSJEnqFANdSZIkSVKnZPke3ZTSsRSzdv0EcB/FzF3nRcSelNKTgV3AZuBm4JxyymtSSh8FngE8Ejg6Iu7py/Nc4HXAg8ADwOsi4l9GlF9VxgpwPXCwXPylEXH9kDyeCrwDOKb86B+BN0TESvn96cB7gOPK738vIq4cv5WakWtbl+13ad+ixwO3R8QZdfIpvxtrm81Dru09QT4j69O3zAeBl4/6fh4yb++Xl/lsoJih8Lcj4vtD8jilzOORZXnXAjsj4v9SSo8E/p6iL98AfBN4VUT8YJL2mkYGbV2Vz5r7a9+yo/qkkduhRjM1Jtf2rtNOKaWjgL8DzgSIiOP6vqs8hs7bjNp7rD6gXHaiMgbyqOpLRm6LNuTa3iml9cBXgC3lot8Bzo+Im2vmk01/kmtbDyxTeT6xRl/ivn1o+TONcVJKjwYuB84AboyIMwfTz1Oud3RXgLdHRIqI04D/Bi4uO5jLgQsi4hTgy8DFfek+AJw+mFm5U70beFZEnA68hWIjH2aMMgCeGhGnl/9GBUw/pNjRHgs8HngKcE5ZxlbgUxQ7xWOBnwX+rbJFZifLto6Ir/a18ekU7fOxuvn0GWebzUOW7V0nn6r69JX1vHJd25Zre/808CfAMyPiVOBfgbeNWIf7gNdHxE9R9BVbgN8vv7sDeHq5X58G/A/wx2s3y0y01tZV+YzxXX+ZVXWt2g5tyLW967TTgxQnS88a8t3IY2hLmm7vsfuAScsYomrbVG2LNmTZ3hFxEHhORDwuIh4HXAm8q24+5NWfZNnWfcuMcz5Rtf+6bz+07MxjHOAe4I3Ab1U1wrxkGehGxPcj4qq+j64BdgBPAA5ExNXl55cBL+pL98XBq0CldeW/o8u/j6E4IRymsowa63BDRNxY/n4v8PVyHaDY+FdHxDXl9w9ExJ11y2jCIrR1Sul44NkUV8AmzicHGbd3nXyq6tM7Yb4IeP2o9POScXv/DLA7HnrR+meBl4xYh5sj4uvl7wcpLvrsKP++PyL2A6SUNgAP46ErsXPVcltX7pNV3w0YWdeq7dCGXNu7TjuVx77PA3uHfFd1DJ27GbT32H3AFGUMrkNVXzJyW7Qh8/a+q2/ZhzO6z12I/iTnth73fGKNvsR9+yEzj3Ei4q4oRgLtq5vvLGQZ6PYrrz68GvgMcBJwS++7iLgDWJ9SekRVHuVy5wHXpZRupbjSsXPE4uOUcVVKaXdK6U/LIRFrrcPxwPMpbu0DPBa4PxUvWN6dUvpASulH1spn1jJta4CXAf8cEd+dIp9a22wecmrvmvms5RLgooGTgdbl1N7AvwNPTCn9eEppHcXFr4etVX5KaTNwbrkO/Z/vBvYAj6G4E9eqFtq6KWPVddR2aEuu7d1UOw05hraqifamXh8waRlV65DVPlwlx/Yuz99uB14MXDiizIXrTzJs6yzPJ5qSYXvD9DFOVrIPdIE/p7gN/t5JM0gpPRz4XeCJEXESxZWhvy13iLpOimK8+dMpAtbKYYIppaMpduB39q7eUYyhfybwCoox7HcD75ygLk3Lra17Xg58cIr0tbbZHGXT3g3m8yLgvojIscPLpr0j4lsUJ0d/RXE1t/cszQMVZW8EPgF8MSIOOSGKYqjpjwL/BZxfpy4zkk1bN61qO7Qou/Zuqp1GHEPbNnV7T9IHNCXTfbhKdu0dEb8KPAr4OPBHk9Yrw22RTVtnfj7RlGzau9REjJOVLCej6kkpvYPiDsXzIuJgeZV5R9/3xwEHY8QD132eDeyNiACIiE+mlD4EHJdSehXwwnK51wGVZUTEbeXPH6aU3k85nCKldAnw82WyF0dEpJS2AP9AcTeyP5C9laJT+06Z9mNMF8hNLce2Lj97MvAIiqEYvc/+sE4+o7ZZm3Jr75TSC8bNJyK+VFGfs4BfTCnd3PfZf6aUfiUivrHGusxMbu1dpv0ExQkOKaUnUUxE8sPB/TsivpSKYckfBX7AiLsHEXF/SunDwPuAt4/TLrPQRluvsU9W1bVWXzLOdpi3HNt7VDsNO06ukc+oY2hrGmzvsfsAxjhWjqjrRH1JTnJu77I+H6CYTGjnovcnubV1SuksRpxPABdQoy/JUW7tXebTRIyTlWwD3ZTS2yjGkj83ivHfAF8DNqeUnhbF+PLzgSvGyO4m4IyU0vFRzHb3DIoHqe+IiLcCb+0rd/2oMlIxvPhAFDMUbgReAOwGiIgLBuq/iWI21Gsi4o0D9fkkcGVK6eiIuBt4DsXQg1bk2NZ9zgU+EhGrV6aa2mZtybS9x86nSkTspG+4Yypm8Ds1Wpp1uaxDju1NSumEiLi97CveTDFZxqj9+0MUE2q8IvpmnU0p/Rjwg4i4p1zu+RQzJrairbaeVM2+ZOR2aEuO7V3VToPHyTXyqTqGtqLh9q7bB9Quo05fkqMc2zultB1YiWLIJxRBxPUT5JPVtsixrdc4nxi7787CuAAAAahJREFUL8lRju3dYIyTlXUrK/n1cymlU4EbgG8BvanWb4qIX0/FlNa7gE08NC32d8t0nwKeBDwa+F/ghoj45fK71wOvpJjp7l6K2e6uZohRZaSUnlJ+vgIcAXwVeO2wk/iU0gUUrw/qP+m8otzpSCm9DHgDxSQGN1G8EmTUM6gzk2tbl99tBm4Hfi4ivrnGeky9zeYh8/auk8/I+gwst0K7rxfKub2vpLiyeiTFldg3RjEpyWAez6W4anoDxUkRwFci4oKU0rMoHntYR/Eoym6K/fuOwXxmLYO2rspnrP21XHZUXzJyO9RrqWbk2t512ymldC1wIsUr5L4D/FNE/M5ax9B5m1F7j9UHlMtOVMZAHpXbZtS2qNtWTci1vVNKp1EEqEdQ9Ls3UfS5366ZTzb9Sa5tPWS5yvOJqv3XffuQ8mca46RipMItwFHANuB7wPsj4k31WqoZWQa6kiRJkiRNahEmo5IkSZIkaWwGupIkSZKkTjHQlSRJkiR1ioGuJEmSJKlTDHQlSZIkSZ1ioCtJkiRJ6hQDXUmSJElSpxjoSpIkSZI65f8BfBPJQfni+UEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize = (15, 15))\n",
    "ax = fig.add_subplot(1,1,1)\n",
    "ax.set_ylabel('Quote ($)', size=20)\n",
    "\n",
    "dates = [x[0] for x in candlesticks]\n",
    "dates = np.asarray(dates)\n",
    "volume = [x[5] for x in candlesticks]\n",
    "volume = np.asarray(volume)\n",
    "\n",
    "candlestick_ohlc(ax, candlesticks, width=1,\n",
    "                 colorup='g', colordown='r')\n",
    "pad = 0.25\n",
    "yl = ax.get_ylim()\n",
    "ax.set_ylim(yl[0]-(yl[1]-yl[0])*pad,yl[1])\n",
    "ax2 = ax.twinx()\n",
    "\n",
    "ax2.set_position(matplotlib.transforms.Bbox([[0.125,0],[0.9,0.32]]))\n",
    "\n",
    "pos = df['Open'] - df['Close']<0\n",
    "neg = df['Open'] - df['Close']>0\n",
    "ax2.bar(dates[pos],volume[pos],color='green',width=1,align='center')\n",
    "ax2.bar(dates[neg],volume[neg],color='red',width=1,align='center')\n",
    "\n",
    "ax2.set_xlim(min(dates),max(dates))\n",
    "yticks = ax2.get_yticks()\n",
    "ax2.set_yticks(yticks[::3])\n",
    "\n",
    "ax2.yaxis.set_label_position(\"right\")\n",
    "ax2.set_ylabel('Volume', size=20)\n",
    "\n",
    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "ax.xaxis.set_major_locator(mticker.MaxNLocator(10))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def removal(signal, repeat):\n",
    "    copy_signal = np.copy(signal)\n",
    "    for j in range(repeat):\n",
    "        for i in range(3, len(signal)):\n",
    "            copy_signal[i - 1] = (copy_signal[i - 2] + copy_signal[i]) / 2\n",
    "    return copy_signal\n",
    "\n",
    "def get(original_signal, removed_signal):\n",
    "    buffer = []\n",
    "    for i in range(len(removed_signal)):\n",
    "        buffer.append(original_signal[i] - removed_signal[i])\n",
    "    return np.array(buffer)\n",
    "\n",
    "signal = np.copy(df.Open.values)\n",
    "removed_signal = removal(signal, 30)\n",
    "noise_open = get(signal, removed_signal)\n",
    "\n",
    "signal = np.copy(df.High.values)\n",
    "removed_signal = removal(signal, 30)\n",
    "noise_high = get(signal, removed_signal)\n",
    "\n",
    "signal = np.copy(df.Low.values)\n",
    "removed_signal = removal(signal, 30)\n",
    "noise_low = get(signal, removed_signal)\n",
    "\n",
    "signal = np.copy(df.Close.values)\n",
    "removed_signal = removal(signal, 30)\n",
    "noise_close = get(signal, removed_signal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "noise_candlesticks = list(zip(mdates.date2num(date),noise_open,\n",
    "                              noise_high,noise_low,noise_close))\n",
    "\n",
    "fig = plt.figure(figsize = (15, 5))\n",
    "ax = fig.add_subplot(1,1,1)\n",
    "ax.set_ylabel('Quote ($)', size=20)\n",
    "\n",
    "candlestick_ohlc(ax, noise_candlesticks, width=1,\n",
    "                 colorup='g', colordown='r')\n",
    "ax.plot(dates, [np.percentile(noise_close, 95)] * len(noise_candlesticks), color = (1.0, 0.792156862745098, 0.8, 0.7),\n",
    "       linewidth=10.0, label = 'overbought line')\n",
    "\n",
    "ax.plot(dates, [np.percentile(noise_close, 10)] * len(noise_candlesticks), \n",
    "        color = (0.6627450980392157, 1.0, 0.6392156862745098, 0.7),\n",
    "       linewidth=10.0, label = 'oversold line')\n",
    "\n",
    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "ax.xaxis.set_major_locator(mticker.MaxNLocator(10))\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x864 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize = (15, 12))\n",
    "ax1 = plt.subplot2grid((3, 1), (0, 0), rowspan=2)\n",
    "\n",
    "ax1.set_ylabel('Quote ($)', size=20)\n",
    "\n",
    "dates = [x[0] for x in candlesticks]\n",
    "dates = np.asarray(dates)\n",
    "volume = [x[5] for x in candlesticks]\n",
    "volume = np.asarray(volume)\n",
    "\n",
    "candlestick_ohlc(ax1, candlesticks, width=1,\n",
    "                 colorup='g', colordown='r')\n",
    "pad = 0.25\n",
    "yl = ax1.get_ylim()\n",
    "ax1.set_ylim(yl[0]-(yl[1]-yl[0])*pad,yl[1])\n",
    "ax2 = ax1.twinx()\n",
    "\n",
    "pos = df['Open'] - df['Close']<0\n",
    "neg = df['Open'] - df['Close']>0\n",
    "ax2.bar(dates[pos],volume[pos],color='green',width=1,align='center')\n",
    "ax2.bar(dates[neg],volume[neg],color='red',width=1,align='center')\n",
    "\n",
    "ax2.set_xlim(min(dates),max(dates))\n",
    "yticks = ax2.get_yticks()\n",
    "ax2.set_yticks(yticks[::3])\n",
    "\n",
    "ax2.yaxis.set_label_position(\"right\")\n",
    "ax2.set_ylabel('Volume', size=20)\n",
    "\n",
    "ax1.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "ax1.xaxis.set_major_locator(mticker.MaxNLocator(10))\n",
    "\n",
    "ax2 = plt.subplot2grid((3, 1), (2, 0))\n",
    "\n",
    "ax2.set_ylabel('Quote ($)', size=20)\n",
    "\n",
    "candlestick_ohlc(ax2, noise_candlesticks, width=1,\n",
    "                 colorup='g', colordown='r')\n",
    "ax2.plot(dates, [np.percentile(noise_close, 95)] * len(noise_candlesticks), color = (1.0, 0.792156862745098, 0.8, 1.0),\n",
    "       linewidth=5.0, label = 'overbought line')\n",
    "\n",
    "ax2.plot(dates, [np.percentile(noise_close, 10)] * len(noise_candlesticks), \n",
    "        color = (0.6627450980392157, 1.0, 0.6392156862745098, 1.0),\n",
    "       linewidth=5.0, label = 'oversold line')\n",
    "\n",
    "ax2.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "ax2.xaxis.set_major_locator(mticker.MaxNLocator(10))\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
